A model on the carbon cycling in Lake Taihu, China

Lacustrine groundwater discharge-derived carbon and nitrogen to regulate biogeochemical processes as revealed by stable isotope signals in a large shallow eutrophic lake

Eutrophic shallow lakes are hotspots of carbon (C) and nitrogen (N) accumulation and transformation, and are increasingly recognized as important sources of greenhouse gases (GHGs: CO2, CH4 and N2O). Lacustrine groundwater discharge (LGD) is a crucial component of the water budget and terrestrial material delivery for lakes, but its interplays with intrinsic CN biogeochemical processes remain less tackled. In this study, C and N ingredients and multiple stable isotopes (δ2H, δ18O, δ13C, and δ15N) were measured seasonally in groundwater, river water and lake water of a large eutrophic shallow lake in eastern China. The results revealed that groundwater is enriched with various forms of C and N that have similar sources and pathways as surface water in the lake and rivers. The isotope balance model also indicated that LGD derived C and N contribute significantly to lake inventories in addition to river runoff. These allochthonous C and N provide extra substrates for related biogeochemical processes, such as algae proliferation, organic matter degradation, methanogenesis and denitrification. Simultaneously, the excess oxygen consumption leads to depletion and hypoxia in the lake, further facilitating the processes of methanogenesis and denitrification. LGD functions not only as an external source of C and N that directly increases GHG saturations, but also as a mediator of internal CN pathways, which significantly affect hypoxia formation, GHG productions and emissions in the eutrophic lake. This study highlights the unrevealed potential regulation of LGD on biogeochemical processes in the eutrophic lake, and underscores the need for its consideration in environmental and ecological studies of lakes both regionally and globally.

Modelling of pH changes in alkaline lakes with water transfer from a neutral river

While water transfer from rivers to alkaline lakes has been proposed to solve lake water level drawdown and ecological degradation problems, its effectiveness for achieving ecological goals is often questionable. A sudden pH decline in alkaline lakes due to water transfer is considered likely to harm the lake ecology. However, it remains unclear to what extent water transfer affects alkaline lake pH. Thus, a three-dimensional numerical model coupling a pH calculation method considering the carbonate balance with the MIKE3 hydrodynamic model was developed to predict pH changes in an alkaline lake. Laboratory and field measurements verified the model reliability. The model accurately simulated the mixed-water pH during water transfer, with a root mean square error of 0.03-0.07 and a coefficient of determination of 0.894-0.998. The model was then applied to predict the pH response to water transfer in Lake Chenghai. The results showed that the pH response to water transfer demonstrated spatial and temporal variability, and a low-pH diffusion zone (pH ≤ 9) formed in the northern parts of the lake during annual water transfer; the effects of water transfer on the pH in the lake were cumulative over time, and the average pH in Lake Chenghai after five years decreased by 0.2 units; strong wind and low inflow could effectively reduce the low-pH diffusion area; and daily thermal stratification of the plateau region threatened the low-pH diffusion area control in Lake Chenghai. Our results provide a new reference for formulating ecological water transfer strategies for alkaline lakes and similar water bodies.

Rising atmospheric CO2 levels result in an earlier cyanobacterial bloom-maintenance phase with higher algal biomass

The effect of rising atmospheric CO₂ on freshwater lakes is a subject of considerable debate. However, it is not clear how rising CO₂ concentration affects cyanobacterial bloom development under potential nutrient limitation conditions and if CO₂ should be taken into account in making nutrient reduction strategy. To fill the knowledge gaps, this study investigated the spatiotemporal variability in aquatic CO₂ concentration (pCO₂) from 2006 to 2016 in Lake Taihu, where cyanobacterial blooms often occurred from late spring to the early fall. Lake Taihu is an atmospheric CO₂ source in May and November, with only 18% and 11% pCO₂-undersaturated areas, respectively. During cyanobacterial bloom in August, 81% of the lake areas are pCO₂-undersaturated, absorbing ~ 0.53 t C/h of atmospheric CO₂. The results demonstrated that CO₂ transfer across air-water interface was important in supporting cyanobacterial bloom development. Besides, Field investigation showed that the chlorophyll a level is significantly positively correlated with supersaturated pCO₂ (>13.56 µmol/L) in May, but pCO₂ decreases with high chlorophyll a levels in August, suggesting that cyanobacterial growth would be promoted by high pCO₂ over a threshold. These observations suggested that the effect of rising atmospheric CO₂ on freshwater lakes and cyanobacterial blooms should be paid attention to. Further, when the N- and P-levels are >0.3 mg/L and >0.02 mg/L, respectively, high-pCO₂ conditions allow a more rapid growth rate of cyanobacteria via improved nutrient-use efficiency. Moreover, cyanobacteria afford maximum N- or P-use efficiency at lower N- or P-concentrations with high CO₂ concentration. This improvement would result in an earlier bloom-maintenance phase and higher cyanobacterial biomass. In this case, nutrient reduction is more imperative under future high CO₂ conditions.

Calibration of a management-oriented greenhouse gas emission model for lakes and reservoirs under different distribution of environmental data

The management-oriented CICLAR lumped model for carbon dynamics and Greenhouse Gas (GHG) emission assessment, is presented. A metaheuristic calibration, through a Pareto based multi-objective particle swarm optimization (PSO), is used to automatically calibrate the model with data from the Capivari reservoir (southern Brazil). Two types of calibration are implemented: (1) with carbon dioxide (CO₂), methane (CH₄) flux, and carbon stock changes, and (2) with synthetic data based on a solution selected from (1). The calibration's performance was assessed by Nash-Sutcliffe and root means squared errors. Three synthetic scenarios are used to analyze the data distribution influence on calibration and GHG fluxes output. The results show that the spread of solutions is higher when the model is calibrated with less data (using only measured values) when compared to the ones obtained from the synthetic data series. Although there are differences between solutions calibrated with different scenarios, all of them characterized the reservoir, through the Global Warming Potential index (GWP), as a sinkhole of equivalent CO₂. Moreover, the similarity among accumulated probability distribution obtained from those different scenarios, suggest that the model can be calibrated regardless of the temporal scopes of measurements.

Migration and transformation of dissolved carbon during accumulated cyanobacteria decomposition in shallow eutrophic lakes: a simulated microcosm study

The decomposition processes of accumulated cyanobacteria can release large amounts of organic carbon and affect the carbon cycling in shallow eutrophic lakes. However, the migration and transformation mechanisms of dissolved carbon (DC) require further study and discussion. In this study, a 73-day laboratory microcosm experiment using suction samplers (Rhizon and syringe) was conducted to understand the migration and transformation of DC during the cyanobacteria decomposition. The decomposition of cyanobacteria biomass caused anoxic and reduction conditions, and changed the acid-base environment in the water column. During the early incubation (days 0–18), a large amount of cyanobacteria-derived particulate organic matter (POM) was decomposed into dissolved organic carbon (DOC) in the overlying water, reaching the highest peak value of 1.82 g L⁻¹ in the treatment added the high cyanobacteria biomass (470 g). After 18 days of incubation, the mineralization of increased DOC to dissolved inorganic carbon (DIC) maintained a high DIC level of overlying water in treatments added cyanobacteria biomass. The treatment added the medium cyanobacteria biomass (235 g) presented the lower DOC/total dissolved carbon ratio than the high cyanobacteria biomass associated with the lower mineralization from DOC to DIC. Due to the concentration differences of DIC at water-sediment interface, the main migration of DIC from pore water to overlying water occurred in the treatment without added cyanobacteria biomass. However, the treatments added the cyanobacteria biomass presented the obvious diffusion of DOC and the low migration of DIC at the water-sediment interface. The diffusive fluxes of DOC at the water-sediment interface increased with the cyanobacteria biomass added, reaching the maximum value of 411.01 mg/(m²·d) in the treatment added the high cyanobacteria biomass. In the overlying water, the group added the sediment and medium cyanobacteria biomass presented a faster degradation of cyanobacteria-derived POM to DOC and a higher mineralization level of DOC to DIC than added the medium cyanobacteria biomass without sediment. Therefore, during accumulated cyanobacteria decomposition, the biomass of accumulated cyanobacteria and sediment property can influence the migration and transformation of DC, playing an important role in carbon cycling in shallow eutrophic lakes.

Predicting Lake Eutrophication Responses to Multiple Scenarios of Lake Restoration: A Three-Dimensional Modeling Approach

To improve the water quality and alleviate the eutrophication of Lake Yangchenghu, the third largest freshwater body within the Lake Taihu basin in China and an important source of drinking water, nutrient reduction strategies should be urgently addressed by decision makers, since virtually no improvement of water quality has taken place since the mid-1990s. Due to the lack of sufficient observation data and simulation results, a vertically compressed three-dimensional numerical model, the EcoTaihu model, was used to study the impact of three restoration measures on the water quality—namely, total nitrogen (TN), total phosphorus (TP) and biomass of phytoplankton (BP)—of Lake Yangchenghu: (i) total nutrient reduction, (ii) intensification of flushing by water transfer, and (iii) spatial adjustment of inflow channels. In particular, the spatial effects of the three restoration measures on the water quality were investigated. The results showed that the EcoTaihu model is applicable to other shallow lakes in China. The water quality responses to the different restoration scenarios showed significant spatio-temporal differences. The reduction of nutrient loads from inflows appeared to be the most effective measure for controlling the eutrophication and algal blooms in Lake Yangchenghu. The effectiveness of water transfer on the improvement of water quality for TN and TP was more influenced by the differences of nutrient concentrations between the transferred water and lake water, rather than flow rate, since no proportionate increase of improvement was observable in the case of larger transferred rates (60 m3 s−1). The spatial narrowing of inflowing rivers in the southwestern lake could preferentially improve the water quality in the southern bay of the western lake, but would also result in a deterioration trend of water quality in the total lake and drinking water abstraction areas.

Will elevated atmospheric CO2 boost the growth of an invasive submerged macrophyte Cabomba caroliniana under the interference of phytoplankton?

The growth of most submerged macrophytes is likely to be limited by the availability of carbon resource, and this is especially true for the obligatory carbon dioxide (CO₂) users. A mesocosm experiment was performed to investigate the physiological, photophysiological, and biochemical responses of Cabomba caroliniana, an invasive macrophyte specie in the Lake Taihu Basin, to elevated atmospheric CO₂ (1000 μmol mol^-1); we also examined the possible impacts of interferences derived from the phytoplankton proliferation and its concomitant disturbances on the growth of C. caroliniana. The results demonstrated that elevated atmospheric CO₂ significantly enhanced the biomass, relative growth rate, and photosynthate accumulation of C. caroliniana. C. caroliniana exposed to elevated atmospheric CO₂ exhibited a higher relative maximum electron transport rate and photosynthetic efficiency, compared to those exposed to ambient atmospheric CO₂. However, the positive effects of elevated atmospheric CO₂ on C. caroliniana were gradually compromised as time went by, and the down-regulations of the relative growth rate (RGR) and photosynthetic activity were coupled with phytoplankton proliferation under elevated atmospheric CO₂. This study demonstrated that the growth of C. caroliniana under the phytoplankton interference can be greatly affected, directly and indirectly, by the increasing atmospheric CO₂.

Integrative Indicator for Assessing the Alert Levels of Algal Bloom in Lakes: Lake Taihu as a Case Study

Algal blooms have recently become one of the most serious environmental problems in eutrophic freshwater ecosystems worldwide. Although many observation and simulation approaches have been applied to predict algal blooms, few studies have addressed the alert levels of algal blooms using integrative indicators in a large lake with multiple service function and significant horizontal heterogeneity. This study developed an integrative indicator assessment system (IIAS) to rank the alert level of algal blooms. In the IIAS, algal biomass, area percentage, distance from drinking water intake points, distance from scenic zones and duration of algal bloom were used as indicators to calculate a comprehensive alert level, which was classified into five grades (Vigilance, Low, Moderate, High, and Severe). Lake Taihu was taken as a case study to assess the comprehensive alert level of algal blooms in 2007 and 2010. The comprehensive alert level showed obvious spatial-temporal patterns, with an acceptable accuracy in Lake Taihu. The comprehensive alert levels were relatively higher in typical phytoplankton subzones than typical hydrophytes subzones and are more sensitive to weight factor in the northern and western subzones where high biomass usually occurs. Case study showed a very good application of the proposed comprehensive alert level assessment methodology, which can be adjusted to predict the degree of hazard of algal blooms in multi-service function large lakes to help the government and decision makers to act to prevent the disaster from algal bloom spreading.

Temporal dynamics and drivers of ecosystem metabolism in a large subtropical shallow lake (lake Taihu)

With continuous measurements of dissolved oxygen, temperature, irradiance, and wind speed, as well as frequent measurements of pH, oxidation-reduction potential, and algal chlorophyll, temporal dynamics and drivers of ecosystem metabolism in a large nutrient-rich shallow lake (Lake Taihu) are tested in this study. The results show that the dissolved oxygen concentrations in the lake fluctuate annually. They increase in autumn and winter with a peak value of 14.19 mg·L⁻¹ in winter, and decrease in spring and summer with a trough value of 6.40 mg·L⁻¹ in summer. Gross primary production (GPP), ecosystem respiration (R), and net ecosystem production (NEP) increase in summer, with their peak values in late summer and autumn, and decrease in winter and spring. Mean values of GPP, R and NEP are 1.75 ± 0.06 (Mean ± SE), 1.52 ± 0.05, and 0.23 ± 0.03 g O₂ m⁻³·d⁻¹, respectively. It is also found that water temperature and surface irradiance are the best predictors of GPP and R, while water temperature (wind speed) has a significantly positive (negative) relationship with NEP. The findings in this study suggest that Lake Taihu is a net autotrophic ecosystem, and water temperature and surface irradiance are the two important drivers of lake metabolism.

A flux-gradient system for simultaneous measurement of the CH4, CO2, and H2O fluxes at a lake-air interface

Inland lakes play important roles in water and greenhouse gas cycling in the environment. This study aims to test the performance of a flux-gradient system for simultaneous measurement of the fluxes of water vapor, CO2, and CH4 at a lake-air interface. The concentration gradients over the water surface were measured with an analyzer based on the wavelength-scanned cavity ring-down spectroscopy technology, and the eddy diffusivity was measured with a sonic anemometer. Results of a zero-gradient test indicate a flux measurement precision of 4.8 W m(-2) for water vapor, 0.010 mg m(-2) s(-1) for CO2, and 0.029 μg m(-2) s(-1) for CH4. During the 620 day measurement period, 97%, 69%, and 67% of H2O, CO2, and CH4 hourly fluxes were higher in magnitude than the measurement precision, which confirms that the flux-gradient system had adequate precision for the measurement of the lake-air exchanges. This study illustrates four strengths of the flux-gradient method: (1) the ability to simultaneously measure the flux of H2O, CO2, and CH4; (2) negligibly small density corrections; (3) the ability to resolve small CH4 gradient and flux; and (4) continuous and noninvasive operation. The annual mean CH4 flux (1.8 g CH4 m(-2) year(-1)) at this hypereutrophic lake was close to the median value for inland lakes in the world (1.6 g CH4 m(-2) year(-1)). The system has adequate precision for CH4 flux for broad applications but requires further improvement to resolve small CO2 flux in many lakes.